Detekcija i raspoznavanje prometnih znakova u slikama

master's thesis

• Title (english): Detection and Recogniton of Trafic Signs in Images
• Author: Josip Mišević
• Mentor: Tomislav Hrkać (mentor)
• Committee member: Tomislav Hrkać (predsjednik povjerenstva)
• Committee member: Zoran Kalafatić (član povjerenstva)
• Committee member: Vladimir Čeperić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2021-07-05, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Autonomna vožnja jedno je od zanimljivijih istraživačkih područja modernog doba, a prepoznavanje prometnih znakova jedno je od važnijih i krucijalnih problema u tom istraživanju. U okviru ovog rada istraženi su algoritmi YOLOv3 i ResNet50 koji surađuju u procesu lokalizacije i klasifikacije prometnih znakova u slikama sa stvarnim uvjetima na cestama. YOLOv3 izvršava lokalizaciju prometnih znakova dok ResNet50 te znakove klasificira u jenu od 43 klase prometnih znakova. Za učenje YOLOv3 i ResNet50 korišteni su skupovi podataka GTSDB i GTSRB koji sadržavaju njemačke prometne znakove. Također, prikazani su rezultati rada naučenih modela.

Abstract (english)

Autonomous driving is one of the most interesting research areas of modern age and traffic signs detection is one of the most important and crucial problem in that research. In this paper, the algorithms YOLOv3 and ResNet50, that cooperate in the process of localization and classification of traffic signs in images with real road conditions, were researched. YOLOv3 performs the traffic signs localization while ResNet50 classifies those signs into one of 43 traffic signs classes. The GTSDB AND GTSRB data sets containing German traffic signs were used to train YOLOv3 and ResNet50. Also, the work results of the trained models were presented.

• Keywords: prometni znak; autonomna vožnja; YOLO; ResNet; prepoznavanje objekata; GTSRB; GTSDB
• Keywords (english): traffic sign; autonomous driving; YOLO; ResNet; object detection; GTSRB; GTSDB
• Language: croatian
• URN:NBN: urn:nbn:hr:168:383409
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-13 13:15:03